Simulation for Appropriate Mean Selection for Can's Approximation Method in Transportation Models
Simulation for Appropriate Mean Selection for Can's Approximation Method in Transportation Models

Summary/Abstract: Classical transportation models aim to minimize the total costs of homogeneous goods transport from supply points to demand points, taking into account unit transportation costs. They constitute a special case of network models and employ a technique based on linear programming. Suggested in 2015 and one of the early distribution methods, Tuncay Can’s Approximation Method (TCAM) is based on the geometric averages of unit transportation costs, although it is stated in the theorem that other means than geometric can be used. The aim of this study is to compare the total costs of a transportation model by solving a problem using geometric, arithmetic, square, and harmonic means based on TCAM. The coefficients of the transportation model were obtained randomly by simulation, and the method was repeated on the problem according to the different means and the appropriate means determined.

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